P
US7743047B2ActiveUtilityPatentIndex 82

Accounting for behavioral variability in web search

Assignee: MICROSOFT CORPPriority: May 8, 2007Filed: Sep 26, 2007Granted: Jun 22, 2010
Est. expiryMay 8, 2027(~0.8 yrs left)· nominal 20-yr term from priority
Inventors:WHITE RYENBRILL ERICDRUCKER STEVENBURGES CHRISTOPHER
G06F 16/9535G06F 16/9538
82
PatentIndex Score
15
Cited by
49
References
18
Claims

Abstract

The concept of variability pertains to whether users exhibit consistent search interaction patterns, for example, in terms of interaction flow or information targeted. Methods are provided for analyzing variability, and then adapting search-related functionality (e.g., processes and/or interfaces) to account for variability characteristics, for example, to account for predictable search interaction behavior.

Claims

exact text as granted — not AI-modified
1. A computer-implemented method for modifying a user's search experience, the method comprising:
 assigning a first set of symbols that represent a first set of actions initiated by the user during creation of a first search trail; 
 assigning a second set of symbols that represent a second set of actions initiated by the user during creation of a second search trail; 
 determining a measure of interaction variance classification that represents an extent to which there are differences between that first and second sets of symbols, wherein determining the measure of interaction variance comprises determining the measure based at least in part on hyperlink navigations initiated by the user and indicated by the first and second sets of symbols; 
 assigning a search behavior classification to the user based at least in part on the measure of interaction variance; and 
 customizing, based at least in part on the assigned search behavior classification, the user's experience with a search process. 
 
   
   
     2. The method of  claim 1 , wherein determining the measure of interaction variance comprises determining the measure based at least in part on data indicative of backward navigations initiated by the user and indicated by the first and second sets of symbols. 
   
   
     3. The method of  claim 1 , wherein the assigned search behavior classification is indicative of a data navigation strategy utilized to arrive at a desired item of information at the end of a data searching process. 
   
   
     4. The method of  claim 3 , wherein the assigned search behavior is a classification selected from a set of behavior classifications that includes a navigator behavior category and an explorer behavior category. 
   
   
     5. The method of  claim 1 , wherein the measure of interaction variance is determined based at least in part on a calculated Levenshtein distance. 
   
   
     6. The method of  claim 1 , wherein the measure of interaction variance is determined based at least in part on a calculated Levenshtein distance between the first and second sets of symbols. 
   
   
     7. The method of  claim 1 , wherein the measure of interaction variance is determined based at least in part on a calculated distance between the first and second sets of symbols. 
   
   
     8. The method of  claim 1 , wherein customizing the user's experience comprises providing a customized search interface. 
   
   
     9. The method of  claim 1 , wherein customizing the user's experience comprises providing a customized search result interface. 
   
   
     10. The method of  claim 1 , wherein customizing the user's experience comprises providing customized advertising. 
   
   
     11. The method of  claim 1 , wherein customizing the user's experience comprises providing customized search tools. 
   
   
     12. A computer-implemented method for modifying a search experience, the method comprising:
 obtaining a collection of data that is a record of user-initiated commands initiated while conducting a search engine-facilitated searching process; 
 determining a measure of interaction variance based on a pattern reflected within the collection of data, the pattern being indicative of a sequence of events indicated in the record, and wherein the measure of interaction variance is a measure based on a comparison of the pattern to at least one other pattern reflected within the collection of data, and wherein determining the measure of interaction variance comprises determining the measure based at least in part on hyperlink navigation indicated in the record of user-initiated commends; and 
 customizing, based at least in part on the measure of interaction variance, the user's experience with a search process. 
 
   
   
     13. The method of  claim 12 , wherein the measure of interaction variance is a measure based on a calculated Levenshtein distance between the pattern and said at least one other pattern. 
   
   
     14. The method of  claim 12 , wherein customizing comprises providing a customized search interface. 
   
   
     15. The method of  claim 12 , wherein customizing comprises providing a customized search result interface. 
   
   
     16. The method of  claim 12 , wherein customizing comprises providing customized advertising. 
   
   
     17. The method of  claim 12 , wherein customizing comprises providing customized search tools. 
   
   
     18. A computer-implemented system for modifying a search experience, comprising:
 a search behavior characterization component that utilizes a computer processor that is a component of a computing device to assign a search behavior classification to a search query based at least in part on a pattern within a set of hyperlink navigations initiated by a user while conducting a search engine-facilitated searching process, wherein assigning a search behavior comprises determining a measure of interaction variance based at least in part on hyperlink navigations as reflected in first and second sets of symbols that represent actions initiated by the user during creation of search trails while conducting the search engine-facilitated searching process; and 
 a search customization component that customizes a user's experience with a search process by providing customized search tools based at last in part on the search behavior classification.

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